Investigation of the minimized pressure drop of four refrigerants in a small channel with genetic algorithm

Abstract

Awareness towards the ozone-depleting Chlorofluorocarbons (CFCs) refrigerants has led researchers to investigate alternative refrigerants which are more environmentally friendly. The miniaturization of evaporators and condensers in heat exchangers of the refrigeration and air-conditioning industry have further challenged the search for new coolants that can fulfill these demands. Of particular concern is the prediction of the pressure drop of the two-phase flow in these heat exchanging devices. This paper presents a preliminary study completed on the minimized frictional pressure drop of four refrigerants at the saturation temperature of 10?C in a horizontal small channel of 1.5 mm diameter; R22, R134A, CO2, and propane. Genetic algorithm (GA) based on a stochastic approach is used to attain the minimization of the frictional pressure drop under the optimized conditions of the vapor quality. The separated model of the Lockhart-Martinelli for two-phase flow is assumed with the laminar-laminar cases investigated using three different versions of the model at three different mass flux conditions. Single-objective optimization with GA has managed to produce the minimized frictional pressure drop for the four refrigerants with CO2 having the lowest frictional pressure drop, almost half that of R22.